CN116091952A - Ground-air integrated intelligent cloud control management system and method based on big data - Google Patents
Ground-air integrated intelligent cloud control management system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of ground-air integrated intelligent cloud control management, in particular to a ground-air integrated intelligent cloud control management system and a ground-air integrated intelligent cloud control management method based on big data, comprising the steps of calling historical operation task execution record information corresponding to each inspection equipment group, respectively capturing and identifying inspection operation nodes existing in the process of inspecting each inspection equipment in each inspection equipment group along each task operation path, and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group; capturing the associated patrol distance value range which is required to be met during collaborative patrol for the patrol equipment which meets the collaborative patrol relation in each patrol equipment group; and acquiring a plurality of inspection equipment groups which currently execute inspection operation tasks in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of the inspection equipment with the cooperative inspection relation in the plurality of inspection equipment groups.
Description
Technical Field
The invention relates to the technical field of ground-air integrated intelligent cloud control management, in particular to a ground-air integrated intelligent cloud control management system and method based on big data.
Background
The space-earth-air integrated remote sensing monitoring service platform is a comprehensive inspection mode which utilizes an offsite supervision mode to find out a suspected target by applying technical means such as remote sensing analysis, information extraction, identification monitoring and the like based on high-resolution space-earth-air integrated remote sensing monitoring service platform, and achieves information acquisition, on-site evidence obtaining and analysis judgment by task management and distribution on-site supervision personnel to the target place, so that the real-time feedback of acquired data is realized, and the target characteristics are timely and comprehensively known. The method helps the user to realize the change from macro supervision to micro supervision, plane supervision to three-dimensional supervision and passive type to active type, and is an important means and method for supervision of industries such as environmental protection, construction, homeland and the like.
The air-ground integrated information network is the front direction of the comprehensive intersection of an air-ground technology and information technologies such as aviation communication, navigation, monitoring and service, and the technology can be applied to a plurality of fields, such as smart city, smart agriculture and smart water affairs, which is the necessary trend of technological development; because the platform relates to state monitoring of multiple devices in actual use, if the devices are unexpected, the platform possibly means that problems occur at the front ends of many data processing, has larger related data range and has stronger dependence on the running state and accuracy of the devices.
Disclosure of Invention
The invention aims to provide a ground-air integrated intelligent cloud control management system and method based on big data, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a ground-air integrated intelligent cloud control management method based on big data comprises the following steps:
step S100: setting a plurality of inspection operation tasks for the target inspection area based on a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification; one patrol job task corresponds to one risk patrol requirement; wherein, a patrol equipment group comprises a plurality of unmanned aerial vehicles, a plurality of unmanned aerial vehicles or a combination of a plurality of unmanned aerial vehicles and unmanned aerial vehicles;
step S200: the method comprises the steps of calling historical operation task execution record information corresponding to each inspection equipment group, capturing and identifying inspection operation nodes existing in the process of inspecting each inspection equipment in each inspection equipment group along each task operation path, dividing each task operation path into road sections to obtain a plurality of corresponding inspection road sections, and extracting and collecting regional characteristic information of each inspection road section;
step S300: based on the information distribution condition of the corresponding patrol road sections of the patrol equipment in each patrol equipment group, identifying and capturing the patrol equipment with the patrol associated road sections in each patrol equipment group, and judging the patrol equipment meeting the cooperative patrol relation for each patrol equipment group;
step S400: capturing the associated patrol distance value range which is required to be met during collaborative patrol for the patrol equipment which meets the collaborative patrol relation in each patrol equipment group;
step S500: and acquiring a plurality of inspection equipment groups which currently execute inspection operation tasks in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of the inspection equipment with the cooperative inspection relation in the plurality of inspection equipment groups.
Further, step S200 includes:
step S201: respectively extracting image sequences uploaded by each inspection device in each inspection device group in the process of inspecting along each task operation path from historical operation task execution record information corresponding to each inspection device group, and respectively extracting characteristic information of inspection areas contained in each image sequence; respectively comparing the similarity of every two adjacent images based on the characteristic information in the image sequences corresponding to the inspection devices;
step S202: when two adjacent images P i And P i+1 When the similarity of the feature information of the corresponding inspection equipment is smaller than the similarity threshold value, judging that the corresponding inspection equipment shoots to obtain an image P i+1 The inspection position is an inspection operation node of the corresponding inspection equipment when the inspection is performed along the corresponding task operation path; defaulting each inspection device to obtain a 1 st image P when shooting 1 The inspection position is the first inspection operation node of each inspection device when inspecting along the corresponding task operation path, and the 1 st image P is obtained from the initial departure position of each inspection device to shooting by default 1 When the inspection position is located, the inspection road section contained in the inspection position is used as a 1 st inspection road section;
step S203: acquiring all the routing inspection operation nodes existing in the task operation paths of all the routing inspection devices; respectively dividing the task operation path of each inspection device into a plurality of inspection road sections based on the inspection operation nodes, and dividing each corresponding image sequence into image subsequences corresponding to each inspection road section; and respectively taking all the characteristic information extracted from the images contained in each image sub-sequence as an area characteristic information set of the inspection road section corresponding to each image sub-sequence.
The range covered by the unmanned aerial vehicle or the unmanned aerial vehicle for the target inspection area is different in the process of inspecting along the task operation path due to different inspection status instructions executed in the process of inspecting along the task operation path, namely the area inspected by the unmanned aerial vehicle or the unmanned aerial vehicle in different time periods in the process of inspecting along the task operation path is changed; the process of dividing the path into a plurality of road sections is to divide the task operation path along which the unmanned aerial vehicle or the unmanned vehicle is positioned into a plurality of inspection road sections covering the same inspection area; that is, a section of the inspection road corresponds to an inspection area.
Further, step S300 includes:
step S301: the method comprises the steps that a certain inspection equipment group is provided with inspection equipment E1 and inspection equipment E2, an inspection road section set corresponding to the inspection equipment E1 is A, and an inspection road section set corresponding to the inspection equipment E2 is B; if a certain inspection road section a exists in the set A j Region characteristic information set Xa of (a) j And a certain inspection road section B in the set B k Is a region feature information set Xb of (a) k Meet Xa j ⊆Xb k Or Xb k ⊆Xa j And the inspection equipment E1 uploads the corresponding region characteristic information set Xa j The time T1 of the image sub-sequence of (2) and the patrol equipment E2 upload the corresponding region characteristic information set Xb k The time T2 of the image sub-sequence of the inspection equipment E1 meets 0 +.ltoreq. |T1-T2|+.β, wherein β is a time difference threshold value, and the inspection equipment E1 is judged to inspect a certain inspection road section a j The time and inspection equipment E2 inspects a certain inspection road section b k When the patrol association exists; judgment a j And b k A group of patrol associated road sections existing between the set A and the set B;
step S302: assuming that the total number of the patrol road segments contained in the set A is n, the total number of the patrol road segments contained in the set B is m, the number of road segment groups with patrol association between the set A and the set B is g, and calculating a patrol association value R=g/[ min (n, m) ]; wherein min (n, m) represents a minimum value taken among n and m; when the patrol association value alpha is less than or equal to R is less than or equal to 1, judging that the patrol equipment E1 and the patrol equipment E2 in a certain patrol equipment group meet the cooperative patrol relationship; wherein alpha is a patrol association threshold.
Further, step S400 includes:
step S401: if the patrol equipment E1 and the patrol equipment E2 in a certain patrol equipment group meet the collaborative patrol relation, any group of patrol association road sections L= { x1, y1} with patrol association between the patrol equipment E1 and the patrol equipment E2 are extracted; wherein x1 is a patrol road section belonging to a patrol road section set of the patrol equipment E1, and y1 is a patrol road section belonging to a patrol road section set of the patrol equipment E2;
step S402: recording the position S1 when the inspection equipment E1 shoots the image subsequence corresponding to x1, recording the position S2 when the inspection equipment E2 shoots the image subsequence corresponding to y1, and extracting the associated inspection distance value required to be satisfied by the inspection equipment E1 and the inspection equipment E2 when inspecting y1 in each historical operation task execution record corresponding to a certain inspection equipment group respectively when inspecting x 1: |s2-s1|;
step S403: in all the historical operation task execution records, capturing the maximum associated patrol distance value and the minimum associated patrol distance value of each group of patrol associated road sections to obtain the associated patrol distance value range which is required to be met by the patrol equipment E1 and the patrol equipment E2 when the collaborative patrol exists on each group of patrol associated road sections.
When the ground and air integrated inspection is realized, different inspection functions which can be realized by different inspection equipment are often needed, each equipment can transmit high-definition images shot during operation back to a platform in real time, and the visual comprehensive analysis is performed on the acquired original data; therefore, when building ground and air integrated inspection, because the collected original data is necessary for comprehensive analysis, the inspection position placement of the equipment is always required to be certain, and the cooperation is the combination of mutually matched technologies.
Further, step S500 includes:
step S501: setting a plurality of inspection equipment groups which currently execute inspection operation tasks in a target inspection area as target inspection equipment groups; in the target inspection equipment group, the inspection equipment with cooperative inspection relation with other inspection equipment is set as first target inspection equipment, and the other inspection equipment is set as second target inspection equipment; extracting the corresponding patrol association road sections and the association patrol distance value ranges of the corresponding two first target patrol equipment meeting the collaborative patrol relationship respectively;
step S502: the method comprises the steps that first target inspection equipment is searched for, in the second target inspection equipment, second target inspection equipment with the task operation path similarity larger than a similarity threshold value corresponding to the first target inspection equipment as candidate equipment, and when an unexpected event occurs to the first target inspection equipment, the candidate equipment is preferentially called to execute operation tasks to be executed by the first target inspection equipment and collaborative inspection to be satisfied;
step S503: when an unexpected event occurs in each first target inspection device, among all the inspection devices serving as candidate devices, the inspection device with the shortest spending time duration required for adjusting to the associated inspection distance value range required to be met between the inspection devices with the cooperative inspection relationship is preferentially selected and used as the final candidate device.
The method also provides a ground-air integrated intelligent cloud control management system for better realizing the method, and the system comprises the following steps: the system comprises a ground-air integrated intelligent cloud control module, a patrol road section management module, a collaborative patrol identification judging module, a collaborative patrol condition identification module and an emergency decision management module;
the ground-air integrated intelligent cloud control module is used for setting a plurality of inspection operation tasks for the target inspection area according to a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification;
the system comprises a patrol road section management module, a storage module and a storage module, wherein the patrol road section management module is used for respectively capturing and identifying patrol operation nodes of each patrol equipment in each patrol equipment group in the process of carrying out patrol along each task operation path, carrying out road section division on each task operation path to obtain a plurality of corresponding patrol road sections, and respectively extracting and collecting regional characteristic information of each patrol road section;
the collaborative inspection identification judging module is used for identifying and capturing the inspection equipment with the inspection related road sections in each inspection equipment group based on the information distribution condition of the inspection road sections corresponding to the inspection equipment in each inspection equipment group, and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group;
the collaborative inspection condition identification module is used for capturing the associated inspection distance value range which needs to be met during collaborative inspection for the inspection equipment meeting the collaborative inspection relation in each inspection equipment group;
the emergency decision management module is used for acquiring a plurality of inspection equipment groups which currently execute inspection operation tasks in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of the inspection equipment with the cooperative inspection relation in the plurality of inspection equipment groups.
Further, the inspection road section management module comprises an inspection operation node management unit and a path division management unit;
the inspection operation node management unit is used for respectively capturing and identifying inspection operation nodes existing in the process of inspecting each inspection device in each inspection device group along each task operation path;
the path division management unit is used for dividing the road sections of the task operation paths to obtain a plurality of corresponding inspection road sections, and extracting and collecting the regional characteristic information of each inspection road section.
Further, the collaborative inspection identification judging module comprises an inspection associated road section identification unit and a collaborative inspection equipment identification unit;
the inspection related road section identification unit is used for identifying and capturing the inspection equipment with the inspection related road section in each inspection equipment group according to the information distribution condition of the inspection road section corresponding to each inspection equipment in each inspection equipment group;
and the collaborative inspection equipment identification unit is used for receiving the data in the inspection associated road section identification unit and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, the generated ground-air integrated inspection equipment group is subjected to monitoring analysis of inspection data, the inspection equipment with a cooperative inspection relationship is captured, the equipment which is actually put into an inspection state and forms the cooperative inspection with other inspection equipment is used as important monitoring equipment, the necessary cooperative condition which is required to be achieved when the cooperative inspection is met is captured, the alternative emergency inspection decision scheme which is used for assisting in generating when the accident occurs is realized based on the realization of the cooperative condition, the loss caused by the occurrence of the inspection accident is reduced, and the inspection accuracy is improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic flow chart of an integrated ground-air intelligent cloud control management method based on big data;
fig. 2 is a schematic structural diagram of an integrated ground-air intelligent cloud control management system based on big data.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: a ground-air integrated intelligent cloud control management method based on big data comprises the following steps:
step S100: setting a plurality of inspection operation tasks for the target inspection area based on a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification; one patrol job task corresponds to one risk patrol requirement; wherein, a patrol equipment group comprises a plurality of unmanned aerial vehicles, a plurality of unmanned aerial vehicles or a combination of a plurality of unmanned aerial vehicles and unmanned aerial vehicles;
step S200: the method comprises the steps of calling historical operation task execution record information corresponding to each inspection equipment group, capturing and identifying inspection operation nodes existing in the process of inspecting each inspection equipment in each inspection equipment group along each task operation path, dividing each task operation path into road sections to obtain a plurality of corresponding inspection road sections, and extracting and collecting regional characteristic information of each inspection road section;
wherein, step S200 includes:
step S201: respectively extracting image sequences uploaded by each inspection device in each inspection device group in the process of inspecting along each task operation path from historical operation task execution record information corresponding to each inspection device group, and respectively extracting characteristic information of inspection areas contained in each image sequence; respectively comparing the similarity of every two adjacent images based on the characteristic information in the image sequences corresponding to the inspection devices;
step S202: when two adjacent images P i And P i+1 When the similarity of the feature information of the corresponding inspection equipment is smaller than the similarity threshold value, judging that the corresponding inspection equipment shoots to obtain an image P i+1 The inspection position is an inspection operation node of the corresponding inspection equipment when the inspection is performed along the corresponding task operation path; defaulting each inspection device to obtain a 1 st image P when shooting 1 The inspection position is the first inspection operation node of each inspection device when inspecting along the corresponding task operation path, and the 1 st image P is obtained from the initial departure position of each inspection device to shooting by default 1 When the inspection position is located, the inspection road section contained in the inspection position is used as a 1 st inspection road section;
step S203: acquiring all the routing inspection operation nodes existing in the task operation paths of all the routing inspection devices; respectively dividing the task operation path of each inspection device into a plurality of inspection road sections based on the inspection operation nodes, and dividing each corresponding image sequence into image subsequences corresponding to each inspection road section; respectively taking all the characteristic information extracted from the images contained in each image sub-sequence as an area characteristic information set of the inspection road section corresponding to each image sub-sequence;
step S300: based on the information distribution condition of the corresponding patrol road sections of the patrol equipment in each patrol equipment group, identifying and capturing the patrol equipment with the patrol associated road sections in each patrol equipment group, and judging the patrol equipment meeting the cooperative patrol relation for each patrol equipment group;
wherein, step S300 includes:
step S301: the method comprises the steps that a certain inspection equipment group is provided with inspection equipment E1 and inspection equipment E2, an inspection road section set corresponding to the inspection equipment E1 is A, and an inspection road section set corresponding to the inspection equipment E2 is B; if a certain inspection road section a exists in the set A j Region characteristic information set Xa of (a) j And a certain inspection road section B in the set B k Is a region feature information set Xb of (a) k Meet Xa j ⊆Xb k Or Xb k ⊆Xa j And the inspection equipment E1 uploads the corresponding region characteristic information set Xa j The time T1 of the image sub-sequence of (2) and the patrol equipment E2 upload the corresponding region characteristic information set Xb k The time T2 of the image sub-sequence of the inspection equipment E1 meets 0 +.ltoreq. |T1-T2|+.β, wherein β is a time difference threshold value, and the inspection equipment E1 is judged to inspect a certain inspection road section a j The time and inspection equipment E2 inspects a certain inspection road section b k When the patrol association exists; judgment a j And b k A group of patrol associated road sections existing between the set A and the set B;
step S302: assuming that the total number of the patrol road segments contained in the set A is n, the total number of the patrol road segments contained in the set B is m, the number of road segment groups with patrol association between the set A and the set B is g, and calculating a patrol association value R=g/[ min (n, m) ]; wherein min (n, m) represents a minimum value taken among n and m; when the patrol association value alpha is less than or equal to R is less than or equal to 1, judging that the patrol equipment E1 and the patrol equipment E2 in a certain patrol equipment group meet the cooperative patrol relationship; wherein alpha is a patrol association threshold;
for example, the patrol road segments included in the set a include a road segment L1, a road segment L2, a road segment L3, and a road segment L4; the tour-inspection road sections contained in the set B comprise a road section Q1, a road section Q2, a road section Q3, a road section Q4, a road section Q5, a road section Q6, a road section Q7, a road section Q8 and a road section Q9; the total number of the patrol road sections contained in the set A is 4, and the total number of the patrol road sections contained in the set B is 9;
the inspection equipment E1 is in inspection association with the inspection equipment E2 in inspection of the road section L1;
the inspection equipment E1 is in inspection association with the inspection equipment E2 in inspection of the road section L2 and the inspection equipment E2 in inspection of the road section Q3;
the inspection equipment E1 has inspection association with the inspection equipment E2 in the inspection Q5 when inspecting the road section L3;
the inspection equipment E1 has inspection association with the inspection equipment E2 in the inspection Q7 when inspecting the road section L4;
in summary, the number of road segment groups of the patrol association existing between the set a and the set B is 4, and the patrol association value r=g/[ min (n, m) ]=4/[ min (4, 9) ]=1; judging that the inspection equipment E1 and the inspection equipment E2 meet the cooperative inspection relation;
step S400: capturing the associated patrol distance value range which is required to be met during collaborative patrol for the patrol equipment which meets the collaborative patrol relation in each patrol equipment group;
for example, the history job task execution record information is extracted 4 times for a certain inspection equipment group; a group of inspection association road sections L1= (x 1, y 1) exist between the inspection equipment E1 and the inspection equipment E2, wherein x1 belongs to an inspection road section set of the inspection equipment E1, and y1 belongs to an inspection road section set of the inspection equipment E2; in the execution records of the 1 st, 2 nd, 3 rd and 4 th historical operation tasks, the associated inspection distance values between the position S1 when the inspection equipment E1 shoots the image subsequence corresponding to x1 and the position S2 when the inspection equipment E2 shoots the image subsequence corresponding to y1 are respectively 200m, 220m, 210m and 205m; so the associated patrol distance value range which is required to be satisfied when the patrol equipment E1 and the patrol equipment E2 carry out collaborative patrol on the patrol associated road section L1= (x 1, y 1) is [200,220];
wherein, step S400 includes:
step S401: if the patrol equipment E1 and the patrol equipment E2 in a certain patrol equipment group meet the collaborative patrol relation, any group of patrol association road sections L= { x1, y1} with patrol association between the patrol equipment E1 and the patrol equipment E2 are extracted; wherein x1 is a patrol road section belonging to a patrol road section set of the patrol equipment E1, and y1 is a patrol road section belonging to a patrol road section set of the patrol equipment E2;
step S402: recording the position S1 when the inspection equipment E1 shoots the image subsequence corresponding to x1, recording the position S2 when the inspection equipment E2 shoots the image subsequence corresponding to y1, and extracting the associated inspection distance value required to be satisfied by the inspection equipment E1 and the inspection equipment E2 when inspecting y1 in each historical operation task execution record corresponding to a certain inspection equipment group respectively when inspecting x 1: |s2-s1|;
step S403: in all the historical operation task execution records, capturing the maximum associated patrol distance value and the minimum associated patrol distance value of each group of patrol associated road sections to obtain an associated patrol distance value range which is required to be met by patrol equipment E1 and patrol equipment E2 when the collaborative patrol exists on each group of patrol associated road sections;
step S500: acquiring a plurality of inspection equipment groups which currently execute an inspection operation task in a target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of inspection equipment with a collaborative inspection relation in the plurality of inspection equipment groups;
wherein, step S500 includes:
step S501: setting a plurality of inspection equipment groups which currently execute inspection operation tasks in a target inspection area as target inspection equipment groups; in the target inspection equipment group, the inspection equipment with cooperative inspection relation with other inspection equipment is set as first target inspection equipment, and the other inspection equipment is set as second target inspection equipment; extracting the corresponding patrol association road sections and the association patrol distance value ranges of the corresponding two first target patrol equipment meeting the collaborative patrol relationship respectively;
step S502: the method comprises the steps that first target inspection equipment is searched for, in the second target inspection equipment, second target inspection equipment with the task operation path similarity larger than a similarity threshold value corresponding to the first target inspection equipment as candidate equipment, and when an unexpected event occurs to the first target inspection equipment, the candidate equipment is preferentially called to execute operation tasks to be executed by the first target inspection equipment and collaborative inspection to be satisfied;
step S503: when an unexpected event occurs in each first target inspection device, among all the inspection devices serving as candidate devices, the inspection device with the shortest spending time duration required for adjusting to the associated inspection distance value range required to be met between the inspection devices with the cooperative inspection relationship is preferentially selected and used as the final candidate device.
The method also provides a ground-air integrated intelligent cloud control management system for better realizing the method, and the system comprises the following steps: the system comprises a ground-air integrated intelligent cloud control module, a patrol road section management module, a collaborative patrol identification judging module, a collaborative patrol condition identification module and an emergency decision management module;
the ground-air integrated intelligent cloud control module is used for setting a plurality of inspection operation tasks for the target inspection area according to a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification;
the system comprises a patrol road section management module, a storage module and a storage module, wherein the patrol road section management module is used for respectively capturing and identifying patrol operation nodes of each patrol equipment in each patrol equipment group in the process of carrying out patrol along each task operation path, carrying out road section division on each task operation path to obtain a plurality of corresponding patrol road sections, and respectively extracting and collecting regional characteristic information of each patrol road section;
the inspection road section management module comprises an inspection operation node management unit and a path division management unit;
the inspection operation node management unit is used for respectively capturing and identifying inspection operation nodes existing in the process of inspecting each inspection device in each inspection device group along each task operation path;
the path division management unit is used for dividing the road sections of each task operation path to obtain a plurality of corresponding patrol road sections, and extracting and collecting the regional characteristic information of each patrol road section respectively;
the collaborative inspection identification judging module is used for identifying and capturing the inspection equipment with the inspection related road sections in each inspection equipment group based on the information distribution condition of the inspection road sections corresponding to the inspection equipment in each inspection equipment group, and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group;
the collaborative inspection identification judging module comprises an inspection associated road section identification unit and a collaborative inspection equipment identification unit;
the inspection related road section identification unit is used for identifying and capturing the inspection equipment with the inspection related road section in each inspection equipment group according to the information distribution condition of the inspection road section corresponding to each inspection equipment in each inspection equipment group;
the collaborative inspection equipment identification unit is used for receiving the data in the inspection associated road section identification unit and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group;
the collaborative inspection condition identification module is used for capturing the associated inspection distance value range which needs to be met during collaborative inspection for the inspection equipment meeting the collaborative inspection relation in each inspection equipment group;
the emergency decision management module is used for acquiring a plurality of inspection equipment groups which currently execute inspection operation tasks in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of the inspection equipment with the cooperative inspection relation in the plurality of inspection equipment groups.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The ground-air integrated intelligent cloud control management method based on big data is characterized by comprising the following steps of:
step S100: setting a plurality of inspection operation tasks for a target inspection area based on a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification; one patrol job task corresponds to one risk patrol requirement; wherein, a patrol equipment group comprises a plurality of unmanned aerial vehicles, a plurality of unmanned aerial vehicles or a combination of a plurality of unmanned aerial vehicles and unmanned aerial vehicles;
step S200: the method comprises the steps of calling historical operation task execution record information corresponding to each inspection equipment group, capturing and identifying inspection operation nodes existing in the process of inspecting each inspection equipment in each inspection equipment group along each task operation path, dividing each task operation path into road sections to obtain a plurality of corresponding inspection road sections, and extracting and collecting regional characteristic information of each inspection road section;
step S300: based on the information distribution condition of the corresponding patrol road sections of the patrol equipment in each patrol equipment group, identifying and capturing the patrol equipment with the patrol associated road sections in each patrol equipment group, and judging the patrol equipment meeting the cooperative patrol relation for each patrol equipment group;
step S400: capturing the associated patrol distance value range which is required to be met during collaborative patrol for the patrol equipment which meets the collaborative patrol relation in each patrol equipment group;
step S500: and acquiring a plurality of inspection equipment groups currently executing an inspection operation task in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution situation of inspection equipment with a collaborative inspection relation in the plurality of inspection equipment groups.
2. The ground-air integrated intelligent cloud control management method based on big data according to claim 1, wherein the step S200 comprises:
step S201: respectively extracting image sequences uploaded by each inspection device in each inspection device group in the process of inspecting along each task operation path from historical operation task execution record information corresponding to each inspection device group, and respectively extracting characteristic information of inspection areas contained in each image sequence; respectively comparing the similarity of every two adjacent images based on the characteristic information in the image sequences corresponding to the inspection devices;
step S202: when two adjacent images P i And P i+1 When the similarity of the feature information of the corresponding inspection equipment is smaller than the similarity threshold value, judging that the corresponding inspection equipment shoots to obtain an image P i+1 The inspection position is an inspection operation node of the corresponding inspection equipment when the inspection is performed along the corresponding task operation path; defaulting each inspection device to obtain a 1 st image P when shooting 1 The inspection position is the first inspection operation node of each inspection device when inspecting along the corresponding task operation path, and the 1 st image P is obtained from the initial departure position of each inspection device to shooting by default 1 When the inspection position is located, the inspection road section contained in the inspection position is used as a 1 st inspection road section;
step S203: acquiring all the routing inspection operation nodes existing in the task operation paths of all the routing inspection devices; respectively dividing the task operation path of each inspection device into a plurality of inspection road sections based on the inspection operation nodes, and dividing each corresponding image sequence into image subsequences corresponding to each inspection road section; and respectively taking all the characteristic information extracted from the images contained in each image sub-sequence as an area characteristic information set of the inspection road section corresponding to each image sub-sequence.
3. The ground-air integrated intelligent cloud control management method based on big data according to claim 2, wherein the step S300 comprises:
step S301: the method comprises the steps that a certain inspection equipment group is provided with inspection equipment E1 and inspection equipment E2, an inspection road section set corresponding to the inspection equipment E1 is A, and an inspection road section set corresponding to the inspection equipment E2 is B; if a certain inspection road section a exists in the set A j Region characteristic information set Xa of (a) j And a certain inspection road section B in the set B k Is a region feature information set Xb of (a) k Meet Xa j ⊆Xb k Or Xb k ⊆Xa j And the inspection equipment E1 uploads the corresponding region characteristic information set Xa j The time T1 of the image sub-sequence of (2) and the patrol equipment E2 upload the corresponding region characteristic information set Xb k The time T2 of the image sub-sequence of the inspection equipment E1 meets 0 +.ltoreq. |T1-T2|+.β, wherein β is a time difference threshold value, and the inspection equipment E1 is judged to inspect a certain inspection road section a j The time and inspection equipment E2 inspects a certain inspection road section b k When the patrol association exists; judgment a j And b k A group of patrol associated road sections existing between the set A and the set B;
step S302: assuming that the total number of the patrol road segments contained in the set A is n, the total number of the patrol road segments contained in the set B is m, the number of road segment groups with patrol association between the set A and the set B is g, and calculating a patrol association value R=g/[ min (n, m) ]; wherein min (n, m) represents a minimum value taken among n and m; when the patrol association value alpha is smaller than or equal to R and smaller than or equal to 1, judging that the patrol equipment E1 and the patrol equipment E2 in the certain patrol equipment group meet a collaborative patrol relationship; wherein alpha is a patrol association threshold.
4. The ground-air integrated intelligent cloud control management method based on big data according to claim 3, wherein the step S400 includes:
step S401: if the patrol equipment E1 and the patrol equipment E2 in a certain patrol equipment group meet the collaborative patrol relation, any group of patrol association road sections L= { x1, y1} with patrol association between the patrol equipment E1 and the patrol equipment E2 are extracted; wherein x1 is a patrol road section belonging to a patrol road section set of the patrol equipment E1, and y1 is a patrol road section belonging to a patrol road section set of the patrol equipment E2;
step S402: recording the position S1 when the inspection equipment E1 shoots the image subsequence corresponding to x1, recording the position S2 when the inspection equipment E2 shoots the image subsequence corresponding to y1, and extracting the associated inspection distance value required to be satisfied by the inspection equipment E1 and the inspection equipment E2 when inspecting y1 in each historical operation task execution record corresponding to a certain inspection equipment group respectively when inspecting x 1: |s2-s1|;
step S403: in all the historical operation task execution records, capturing the maximum associated patrol distance value and the minimum associated patrol distance value of each group of patrol associated road sections to obtain the associated patrol distance value range which is required to be met by the patrol equipment E1 and the patrol equipment E2 when the collaborative patrol exists on each group of patrol associated road sections.
5. The ground-air integrated intelligent cloud control management method based on big data according to claim 4, wherein the step S500 comprises:
step S501: setting a plurality of inspection equipment groups currently executing inspection operation tasks in the target inspection area as target inspection equipment groups; in the target inspection equipment group, the inspection equipment with cooperative inspection relation with other inspection equipment is set as first target inspection equipment, and the other inspection equipment is set as second target inspection equipment; extracting the corresponding patrol association road sections and the association patrol distance value ranges of the corresponding two first target patrol equipment meeting the collaborative patrol relationship respectively;
step S502: the method comprises the steps that first target inspection equipment is respectively searched for second target inspection equipment, the similarity of task operation paths of which is larger than a similarity threshold value corresponding to the first target inspection equipment, in the second target inspection equipment, as alternative equipment, when unexpected events occur in the first target inspection equipment, the alternative equipment is preferentially called for executing operation tasks to be executed by the first target inspection equipment and collaborative inspection to be satisfied;
step S503: when an unexpected event occurs in each first target inspection device, among all the inspection devices serving as candidate devices, preferentially calling the inspection device with the shortest spending time for adjusting to the associated inspection distance value range which needs to be met between the inspection devices with the collaborative inspection relationship, and taking the inspection device as the final candidate device.
6. A ground-air integrated intelligent cloud control management system applying the ground-air integrated intelligent cloud control management method based on big data as set forth in any one of claims 1-5, the system comprising: the system comprises a ground-air integrated intelligent cloud control module, a patrol road section management module, a collaborative patrol identification judging module, a collaborative patrol condition identification module and an emergency decision management module;
the ground-air integrated intelligent cloud control module is used for setting a plurality of inspection operation tasks for a target inspection area according to a plurality of risk inspection requirements existing in the target inspection area; building a patrol equipment group according to a task template corresponding to each patrol operation task, and planning to obtain a corresponding task operation path according to the operation requirement corresponding to each patrol equipment; controlling each inspection equipment group to execute multi-line automatic inspection in a target inspection area, and carrying out risk inspection identification;
the inspection road section management module is used for capturing and identifying inspection operation nodes of each inspection device in each inspection device group in the process of inspecting along each task operation path, dividing road sections of each task operation path to obtain a plurality of corresponding inspection road sections, and extracting and collecting regional characteristic information of each inspection road section;
the collaborative inspection identification judging module is used for identifying and capturing the inspection equipment with the inspection related road sections in each inspection equipment group based on the information distribution condition of the inspection road sections corresponding to the inspection equipment in each inspection equipment group, and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group;
the collaborative inspection condition identification module is used for capturing the associated inspection distance value range which needs to be met during collaborative inspection for the inspection equipment meeting the collaborative inspection relation in each inspection equipment group;
the emergency decision management module is used for acquiring a plurality of inspection equipment groups currently executing an inspection operation task in the target inspection area, and assisting in generating a corresponding decision scheme when an unexpected event occurs based on the distribution condition of inspection equipment with a collaborative inspection relation in the plurality of inspection equipment groups.
7. The ground-air integrated intelligent cloud control management system according to claim 6, wherein the patrol road section management module comprises a patrol operation node management unit and a path division management unit;
the inspection operation node management unit is used for capturing and identifying inspection operation nodes existing in the process of inspecting each inspection device in each inspection device group along each task operation path;
the path division management unit is used for dividing the road sections of the task operation paths to obtain a plurality of corresponding inspection road sections, and extracting and collecting the regional characteristic information of each inspection road section.
8. The ground-air integrated intelligent cloud control management system according to claim 6, wherein the collaborative inspection identification judging module comprises an inspection associated road section identification unit and a collaborative inspection equipment identification unit;
the inspection related road section identification unit is used for identifying and capturing the inspection equipment with the inspection related road section in each inspection equipment group according to the information distribution condition of the inspection road section corresponding to each inspection equipment in each inspection equipment group;
the collaborative inspection equipment identification unit is used for receiving the data in the inspection association road section identification unit and judging the inspection equipment meeting the collaborative inspection relation for each inspection equipment group.
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